Demographic and Socioeconomic Factors Associated to Fruits and Vegetables Consumption in Elderly Europeans: A Systematic Review

Several epidemiological studies stress the association between a diet based on high fruits and vegetables intake and a better health condition. However, elderly Europeans cannot manage the recommended fruits and vegetables consumption. This systematic review aims to explore the main factors related to fruits and vegetables consumption in elderly Europeans. We conducted literature searches on Medline, Scopus, and Web of Science from inception to May 2022. Published articles including data related to certain fruits and vegetables consumption among elderly Europeans were selected. The New Castle-Ottawa Scale and National Heart, Lung, and Blood Institute tools were used for methodological quality assessment by two authors independently. A total of 60 articles were retrieved, and data from twenty-one high-quality cross-sectional studies and five moderate-to-high-quality cohort studies, including a total of 109,516 participants, were synthesized. Associated factors mostly analyzed were those relating to demographic and socioeconomic status, such as sex, age, marital status, educational level, and income. However, the findings show a high discrepancy. Some evidence suggests a possible positive association, while other evidence shows an inverse or no association at all. The relationship between demographic and socioeconomic factors with fruits and vegetables consumption is not at all clear. More epidemiological studies with an appropriate design and corresponding statistical methods are required.


Introduction
In the next 20 years, an increase by about 45% of the population aged 65 years and over is expected in Europe [1]. This demographic change will have an effect on the incidence of chronic diseases, considering the association between age and multiple health outcomes such as cardiovascular, endocrine, and neurological diseases and osteoporosis [2,3]. Therefore, this situation calls for a major effort to ensure quality of life in our older population. Covering basic needs such as ensuring the consumption of healthy food is the basis for dignified and independent ageing.

Eligibility Criteria and Research Strategy
This review was conducted to explore the main factors associated with fruits and vegetables consumption. The research strategy was built according to the PECOS statement: -Population: non-institutionalized elderly people aged between 55 and 80 years old; -Exposure: factors associated to fruits and vegetables intake (gender, age, SES, etc.); -Comparators: lowest fruits and vegetables intake; -Outcome: fruits and vegetables consumption (quantity and variety); -Study design: quantitative and qualitative observational studies.
Three databases, Medline, Scopus, and Web of Science, were used for the research. The selection of the included studies was conducted based on previously set selection criteria: (1) quantitative and qualitative observational studies including cross-sectional and cohort design; (2) published from the inception of each database to May 2022; (3) in Spanish, English, or French; (4) conducted in Europe; (5) including non-institutionalized elderly population without specific diseases; (6) analyzing factors associated to fruits and vegetables consumption. Gray literature, books, communications, and reviews were excluded.

Quality Assessment
The quality of the selected studies was assessed independently by two authors (M.K. and C.O.-R), and discrepancies were solved through discussion with a third researcher. In accordance with the study design, three assessment tools were employed. Cross-sectional studies were evaluated using National Heart, Lung, and Blood Institute (NIHLBI) tools [15]. Two items related to a longitudinal design were not considered for cross-sectional studies: (1) sufficient time frame to see an association and (2) participants who did not engage in follow-up. Twelve items related to the research question, selection of participants, participation rate, exposure, and outcome assessment, and confounders control was also assessed. Classification of the studies was carried out based on the following cut-off scores: "0-4, low quality", "5-9, moderate quality", and "10-12, high quality". For cohort studies, the Newcastle-Ottawa tool was used to assess the level of quality [16]. The scale consists in assessing 8 items related to selection, comparability, and outcome. A maximum of 9 stars can be assigned to each study (2 stars can be assigned to the item of comparability). The considered scores were "≥8 stars, high quality", "6 to 7, moderate quality", "≤5 stars, low quality".

Data Extraction and Data Synthesis
Two reviewers (M.K. and C.O.-R) performed the data extraction using a predefined form. The principal information included country, year of publication, study design, sampling strategy, sample size, eligibility criteria, participant characteristics, principal outcome (dietary pattern, diet quality, fruits and vegetables quantity), assessment methods, exposure (associated factors such as socioeconomic factors, educational level, age, sex, and others), controlling factors, and principal outcomes. Different factors associated with higher or lower consumption of fruits and vegetables were explored, and a narrative synthesis of the consulted articles was conducted for highquality cross-sectional studies and moderate-to-high-quality cohorts.

Literature Research
A total of 10,046 articles were retrieved. After removing duplicates, title and abstract screening was carried out, and 111 articles meeting the eligibility criteria were selected for full-text screening (further details in Table S1. Supplementary Material). Finally, 60 records published between 1995 and 2021 were included in our review ( Figure 1).

Quality Assessment of Included Studies
Methodological quality was assessed for 60 selected records. The NHLBI quality tool was applied for 51 cross-sectional studies, and the Newcastle-Ottawa Scale for nine cohorts. Regarding cross-sectional studies, 41.21% (n = 21) showed high quality, and 58.8% (n = 30) moderate quality. Weaknesses were mostly observed for the following items: (1) sample-size justification, power, variance, and effect estimation; (2) exposure measurement before the outcome measurement; (3) measurement of the outcome more than once, (4) blinding exposure ( Figure 2 and Table S3). From the nine cohort studies assessed, only one showed high quality, while the percentage of low and moderate quality was similar at 44.44% (n = 4) ( Table 1).

Quality Assessment of Included Studies
Methodological quality was assessed for 60 selected records. The NHLBI quality tool was applied for 51 cross-sectional studies, and the Newcastle-Ottawa Scale for nine cohorts. Regarding cross-sectional studies, 41.21% (n = 21) showed high quality, and 58.8% (n = 30) moderate quality. Weaknesses were mostly observed for the following items: (1) sample-size justification, power, variance, and effect estimation; (2) exposure measurement before the outcome measurement; (3) measurement of the outcome more than once, (4) blinding exposure ( Figure 2 and Table S3). From the nine cohort studies assessed, only one showed high quality, while the percentage of low and moderate quality was similar at 44.44% (n = 4) (

Quality Assessment of Included Studies
Methodological quality was assessed for 60 selected records. The NHLBI quality tool was applied for 51 cross-sectional studies, and the Newcastle-Ottawa Scale for nine cohorts. Regarding cross-sectional studies, 41.21% (n = 21) showed high quality, and 58.8% (n = 30) moderate quality. Weaknesses were mostly observed for the following items: (1) sample-size justification, power, variance, and effect estimation; (2) exposure measurement before the outcome measurement; (3) measurement of the outcome more than once, (4) blinding exposure ( Figure 2 and Table S3). From the nine cohort studies assessed, only one showed high quality, while the percentage of low and moderate quality was similar at 44.44% (n = 4) ( Table 1).    The asterisks Corresponds to stars described in the methodology of newcastle Ottawa scale.

Characteristics of the Studies
For data synthesis, cross-sectional studies of high quality were analyzed. Regarding cohort studies, moderate-to-high-quality articles were examined as only one study showed high quality. A total of 26 articles were analyzed, including five cohorts and twenty-one cross-sectional. The mean characteristics of cohort studies were summarized in Table 2, and those of cross-sectional ones in Table 3. The distribution of studies according to the geographic area was as follows: five studies were conducted in the United Kingdom (UK) [18,19,[26][27][28], five in the Netherlands [29][30][31][32][33], four in France [20,22,34,35], two in Spain [36,37], Greece [38,39] and Portugal [40,41], and only one study was conducted in each of these countries: Finland, Switzerland, Germany, Italy, and Norway. Finally, one study was multisite, conducted in France, Italy, and the UK.         Outcomes were averaged by fruits and vegetables consumption or adherence to fruits and vegetables guidelines. Demographic factors were the principal exposure analyzed in eighteen articles. Eleven records report an association between socioeconomic status (SES) and fruits and vegetables consumption. Sample size ranged from 3392 [19] to [22] in cohort studies, and from 98 [37] to [29] in cross-sectional studies.

Association between Demographic Determinants and Fruits and Vegetables Consumption
The association between age and fruits and vegetables consumption is not at all clear. Some studies show an inverse association [20,29,36], other studies report no association at all [35,44]. The effect of age on fruits and vegetables is not the same [45]. Moreover, outcomes can differ depending on geographic area and sex [41,43]. Regarding sex, being female was associated with high fruits and vegetables consumption [20,26,31,33,37]. However, two records do not report any association [39,43]. The findings from one study suggest a significant high fruits consumption in men [45]. Regarding marital status and social isolation determinants, we were not able to clearly define the relationship with fruits and vegetables consumption. High variation was observed in the social situation definition, which makes the comparison less evident. Regarding geographic determinants, fruits and vegetables consumption can be significantly different when comparing countries or regions [28,43]. However, the differences between rural and urban areas are not clear (Table 4).
Other determinants were collected for this inventory (psychological state, smoking habits, cooking skills, and chewing ability). The available data were not sufficient to establish a conclusion regarding these factors (Table S4). Dijkstra et al. stress the price of fruits and vegetables and taste preferences as the principal barriers related to consumption [32]. Wandle's findings relate fruits consumption to preferences, and vegetables consumption to nonfeasting meal patterns [47].

Association between Socioeconomic Status (SES) Predictors and Fruits and Vegetables Consumption
Outcomes related to the association between SES predictors and fruits and vegetables consumption were inconsistent. Some studies show a positive association between educational level [23,24,29,38], economic situation [24,37,39], and fruits and vegetables consumption. However, other studies show an inverse association between educational level and fruits and vegetables consumption [22,41] and no association with economic status [30,45]. Similarly, discrepancies were observed for employment status [17,22]. Outcomes can differ depending on sex [41,44] or geographic area [43] (Table 5). Men showed high intake of fruits and vegetables (not statistically significant)  Age was associated with lower consumption of raw vegetables Men consumed more raw vegetables, while women had higher consumption of raw fruits and cooked fruits or vegetables Living alone was associated with low consumption of fruits and vegetables Rossum et al., 2000 [33] (Netherlands) Women consumed more fruits than men did Johnson et al., 1998 [27] (UK) Vegetables consumption decreased significantly with age Low fruits and vegetables consumption was particularly associated with being male Singleness was associated with lower fruits and vegetables consumption in men Living in a rural area was associated with higher compliance with 5 fruits and vegetables consumption/day

Discussion
This review proposes an inventory of 21 high-quality cross-sectional studies and five cohort studies with moderate to high quality reporting about associated factors to fruits and vegetables consumption in elderly people. The main associated factors analyzed in the available scientific evidence were age, sex, and determinants related to marital status and SES. Although the association between these determinants and fruit and vegetable consumption may be clear in some age groups, such as in children and adolescents, this association shows greater diversity in older Europeans. On the other hand, other factors such as liking, accessibility, psychological changes, functional disabilities and health consciousness, and knowledge and awareness of current recommendations were suggested as possible factors [49,50].
A scoping review suggests some differences in fruits and vegetables consumption especially by geographic area, socioeconomic status, marital status, and gender. Fruit and vegetables consumption varies widely according to geographical area. In some countries such as the United States, Thailand, and Baltic countries, living in a rural area was negatively associated with fruits and vegetables consumption [50,51]. However, this association does not seem accurate in all European populations. Several countries, especially those in the Mediterranean basin, such as Italy, Spain, and Greece, show high fruits and vegetables intake [43,49]. Being married and a high socioeconomic status were positively associated with fruits and vegetables consumption. Regarding gender, women tend to comply better with the recommendations than men do [14]. On the other hand, although gender shows a difference in consumption among the younger group, this relationship was not distinctive among the oldest group [51]. Articles excluded for quality show similar results regarding variability in the association of determinants such as gender and geographic area on fruits and vegetables consumption. A comparison between geographic areas, defined as countries or regions, shows some differences [52,53]. However, no difference was observed between rural and urban areas [54].
Our conclusions related to advanced age were similar to those reported previously for adults [55]. However, outcomes from other studies show a potential positive association between determinants such as income, educational level, and physical activity [27,[56][57][58]. Nevertheless, no difference was observed for age, gender, and smoking status in a crosssectional study of 504 Iranian older adults [58]. These outcomes are opposed to Baker et al.'s findings, as their outcomes on 1024 UK older adults confirm that men consume less fruits and vegetables than women do [59].
This inconsistency between various findings may be explained by the particular characteristics of participants, as belonging to different groups according to geographic area, income level, education, and culture. Determinants are typically affected by other factors. Cooking skills in British men was associated to a better consumption of fruits and vegetables [60], although other factors such as living alone may influence the ability to cook. Moreover, this cannot be generalized to other cultures or countries. On the other hand, living in some geographic areas showing less fruits and vegetables intake, such as a rural area or shanty town, is usually related to the economic situation and educational level. Differences between countries may also be related to cultural factors, as would be the case with the Mediterranean diet.
Other factors may be related to the applied study design and statistical method. Furthermore, this relationship does not look the same for fruits as it does for vegetables. This fact further complicates the comparison, since some studies evaluate fruits and vegetables together and others, separately. Finally, like Niklett et al., we also observed a deficiency in studies that specifically analyze the factors associated to fruits and vegetables consumption [14].
Our systematic review has some strengths: (1) the research was extensive and included a large list of possible associated factors, (2) only high-quality evidence was included in the results, (3) reporting review was conducted according to the PRISMA checklist. However, some limitations must be taken into account when interpreting the results. At the methodological level, the review protocol was not published previously, and the included articles were not selected in pairs. However, quality assessment and data extraction were performed by two authors independently. The fact that the associated factors were selfreported by participants is another limitation to take into account. Furthermore, it should be noted that different patterns of diet can be observed depending on the stage of aging: young-old or old-old [61].
Identifying the consumption patterns and associated factors allows us to determine population groups at risk of nutritional deficiencies. This would help to guide public health campaigns in promoting healthy lifestyles and habits. Our findings provide a summary of data obtained in the high-quality research. However, conducting second-level epidemiological studies is a necessity in order to draw more definite conclusions regarding the factors associated to fruits and vegetables consumption. Longitudinal studies may help to define a causal pathway.

Conclusions
Our review provides a summary of moderate-to-high-quality scientific evidence reporting data about potential associated factors to fruits and vegetables intake in elderly Europeans. Fruits and vegetables consumption may be associated to the analyzed predictors. However, confirmation of the presence of a causal relationship was not feasible due to the high level of inconsistency in the available findings. To draw stronger conclusions, more studies with an adequate design and hypothetical constructs such as health consciousness, psychological changes, independence level, and availability and diversity in local shops would be required to explore the factors associated to fruits and vegetables consumption.